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Deepset vs Selectpdf

Selectpdf scores higher on the AgentReady, 47/100 against 44/100. They differ on 10 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Deepset. Deepset is a company that provides Haystack, an open platform to build, run, and govern AI agents and applications.

Selectpdf. SelectPdf is a battle-tested HTML to PDF toolkit providing a .NET Library for self-hosted embedding and a REST API for any language.

Where Deepset is ahead

Deepset passes mcp discoverable, and Selectpdf does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds adopt: cli available and mcp integration available. Selectpdf misses those.

And on operate, observable execution. Selectpdf misses it.

Where Selectpdf is ahead

Selectpdf passes clear product positioning and public docs discoverable, and Deepset does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented. Deepset misses it.

And on adopt, fast time to first request, copyable quickstart and official typescript sdk. Deepset misses those.

What neither does

Both fail llms-full.txt / full agent docs, structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover is whether an agent can find the product at all without being told it exists. Selectpdf leads 80 to 67. Deepset misses clear product positioning, public docs discoverable, llms-full.txt / full agent docs; Selectpdf misses llms-full.txt / full agent docs, mcp discoverable.

Understand. Selectpdf leads 31 to 23. Deepset misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Selectpdf misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Selectpdf leads 52 to 50. Deepset misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, fast time to first request, copyable quickstart, official typescript sdk; Selectpdf misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, cli available, mcp integration available.

Operate. Deepset leads 35 to 24. Deepset misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified; Selectpdf misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution, agent compatibility verified.

Pricing

Deepset starts at $0/mo and has a free tier. Selectpdf starts at $19/mo and has a free tier.

Signal by signal

Which to pick

Selectpdf clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Deepset and Selectpdf. Alternatives to each: Deepset, Selectpdf.

An agent can fetch this as data: POST /v1/compare {"slugs": ["deepset", "selectpdf"]}